Robots Can Now Pick Up Any Object After Inspecting It

Dense Object Nets is a system that lets robots inspect random objects and visually understand them enough to accomplish specific tasks without having seen them previously.

Credit: Tom Buehler/CSAIL

Researchers at the Massachusetts Institute of Technology's (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL) have created Dense Object Nets (DON), a system that lets robots inspect random objects and visually understand them enough to accomplish specific tasks without having seen them previously.

The DON system looks at objects as collections of points that serve as a kind of visual roadmap. This approach allows robots to better understand and manipulate items; they can even pick up a specific object among a clutter of similar ones.

The system creates a series of coordinates on a given object to give the robot a better understanding of what is needed to grasp it, and where.

MIT researcher Pete Florence said, "A system like this that can understand objects' orientations could just take a picture and be able to grasp and adjust the object accordingly."

DON has potential applications in manufacturing settings, performing tasks such as picking items off a shelf, and in homes completing chores such as cleaning.